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ICDM
2006
IEEE
226views Data Mining» more  ICDM 2006»
14 years 2 months ago
Converting Output Scores from Outlier Detection Algorithms into Probability Estimates
Current outlier detection schemes typically output a numeric score representing the degree to which a given observation is an outlier. We argue that converting the scores into wel...
Jing Gao, Pang-Ning Tan
ICDM
2003
IEEE
225views Data Mining» more  ICDM 2003»
14 years 2 months ago
Combining the web content and usage mining to understand the visitor behavior in a web site
A web site is a semi structured collection of different kinds of data, whose motivation is show relevant information to visitor and by this way capture her/his attention. Understa...
Juan D. Velásquez, Hiroshi Yasuda, Terumasa...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 9 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
KDD
2003
ACM
113views Data Mining» more  KDD 2003»
14 years 9 months ago
Mining unexpected rules by pushing user dynamics
Unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. In this paper, we study three important issues...
Ke Wang, Yuelong Jiang, Laks V. S. Lakshmanan
PAKDD
2011
ACM
419views Data Mining» more  PAKDD 2011»
12 years 11 months ago
DISC: Data-Intensive Similarity Measure for Categorical Data
Abstract. The concept of similarity is fundamentally important in almost every scientific field. Clustering, distance-based outlier detection, classification, regression and sea...
Aditya Desai, Himanshu Singh, Vikram Pudi